| BH {sgof} | R Documentation |
Benjamini-Hochberg (BH) multiple testing procedure
Description
Performs the Benjamini-Hochberg FDR-controlling method for multiple hypothesis testing.
Usage
BH(u, alpha = 0.05)
Arguments
u |
A (non-empty) numeric vector of p-values. |
alpha |
Numeric value. The significance level of the test. |
Details
The function BH allows for the application of the Benjamini and Hochberg (1995) false discovery rate controlling procedure. The false discovery rate is estimated by the simple method proposed by: Dalmasso, Broet, Moreau (2005), by taking n=1 in their formula.
Value
A list containing the following values:
Rejections |
The number of effects declared by the BH procedure. |
FDR |
The estimated false discovery rate. |
Adjusted.pvalues |
The adjusted p-values. |
data |
The original p-values. |
alpha |
The specified significance level for the test. |
call |
The matched call. |
Author(s)
Irene Castro Conde and Jacobo de Uña Álvarez
References
Benjamini Y and Hochberg Y (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B (Methodological) 57, 289–300.
Dalmasso C, Broet P and Moreau T (2005). A simple procedure for estimating the false discovery rate. Bioinformatics 21:660–668
See Also
Examples
res<-BH(Hedenfalk$x)
summary(res) #number of rejected nulls, estimated FDR
plot(res) #adjusted p-values